Data Engineer Principal

What you will do

• Lead the strategy, architecture, and evolution of enterprise data platforms that support scalable analytics, AI, and business intelligence outcomes.
• Partner with business leaders, product teams, and technical stakeholders to translate complex requirements into high-value data solutions.
• Design and optimize data lake, lakehouse, data warehouse, and cloud-based architectures to improve accessibility, quality, and performance.
• Deliver resilient and reusable data pipelines that accelerate decision-making and reduce time-to-insight.
• Champion data governance, security, compliance, and quality standards for trusted enterprise data assets.
• Drive continuous improvement to enhance scalability, operational efficiency, cost optimization, and platform performance.
• Provide technical leadership, mentoring, and architectural guidance to data engineering teams while fostering engineering excellence.
• Enable executive and business-critical decisions through integration and delivery of data from diverse enterprise systems.

What you bring

• Proven ability to architect and deliver enterprise-scale data platforms, data models, and cloud-based analytics solutions that support business growth and innovation.
• Deep expertise in modern data engineering, including scalable pipeline development, data integration, data modeling, distributed processing, and cloud-native architectures.
• Strong leadership and stakeholder management skills to influence cross-functional teams, navigate ambiguity, and align technical solutions to business outcomes.
• Advanced knowledge of data governance, security, compliance, and modern software engineering practices, including Agile, DevSecOps, CI/CD, and automation.
• 10+ years of progressive experience in data engineering, data architecture, analytics engineering, or a closely related field, including leading complex enterprise data solutions.
• Demonstrated experience delivering enterprise data, analytics, or AI solutions in large, complex manufacturing and supply-chain environments, across one or more functions such as planning, procurement, manufacturing, inventory, logistics, engineering, aftermarket, commercial, finance, or related operational areas.
• Hands-on expertise with SQL and Python/PySpark, plus data modeling, scalable pipeline design, data integration, and distributed/cloud data platforms.
• Experience designing, building, and operating batch and streaming or near-real-time data pipelines with orchestration, reliability, monitoring, recovery, scalability, and performance in mind.
• Experience integrating data across complex enterprise source systems including ERP/operational systems, legacy databases, APIs, cloud platforms, event streams, IoT/telemetry sources, and structured or unstructured data.
• Strong data modeling experience, including relational and dimensional modeling, fact and dimension structures, star or snowflake schemas, conformed dimensions, and modeling patterns supporting analytics, operational, and AI use cases.
• Experience building reusable data engineering frameworks, shared data foundations, enterprise data models, and governed data products for multiple use cases.
• Experience with enterprise data platforms such as Databricks, Snowflake, and Azure data services or comparable cloud technologies.
• Ability to lead solutions through the full lifecycle, from business discovery and requirements through exploration, architecture, implementation, deployment, monitoring, optimization, and ongoing support.
• Ability to collaborate across Business, Data Science, AI Engineering, Analytics, Enterprise Architecture, and platform and application teams.
• Demonstrated understanding of data engineering and architecture foundations enabling advanced analytics, machine learning, GenAI, and other AI-enabled solutions while maintaining standards for data quality, governance, security, scalability, reuse, performance, and cost.

Technologies

• SQL, Python, PySpark
• Agile, DevSecOps, CI/CD
• Data lake, Lakehouse, Data warehouse
• Databricks, Snowflake, Azure data services
• ERP, APIs, Event streams
• IoT/telemetry sources
• Batch and streaming data pipelines, Near-real-time data pipelines, Streaming
• Distributed processing, Cloud-native architectures

Education and compliance

College, university, or equivalent degree in a relevant technical discipline, or relevant equivalent experience is required. This position may require licensing to comply with export controls or sanctions regulations.

Relocation package: Yes.

Estimated salary range note: The salary range provided is a good faith estimate; the final offer will be determined after considering relevant factors, including qualifications and experience.

REQID: 2438266